Accurate information about the human settlements without electricity is essential for monitoring the areas deprived of access to electricity and to end the darkness. Motivated by the 2021 IEEE GRSS Data Fusion Contest organized by the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society (GRSS), the objective of this research was to assess the human settlements without electricity for areas in and around Bangalore City. We used multimodal and multitemporal data of the year 2019 with 27 layers such as Landsat-8 OLI bands, Sentinel-1 C Band (SAR data) with VV and VH polarization, spectral indices (EVI, NDVI, MNDWI, NDBI, NDMI, BSI, SAVI, IBI, BuEI and SoEI), Texture parameters (DISS, Entropy and Angular Second Moment), Topological data (slope and elevation), and land surface temperature to detect land use map with urban builtup, vegetation, water and barren land classes with a spatial resolution of 30 m using object-based Random Forest algorithm. To overcome the computational limitations, all the analyses were carried out in Google Earth Engine (GEE) cloud-based platform that has planetary-scale analysis capabilities. Overall, 39 experiments on classification were carried out with various combinations of feature vectors to obtain the most accurate land use map with 4 classes. Composite of Landsat bands and advantages of other spectral indices with thresholds rendered the highest classification accuracy of 93.49%. The final mapping results of human settlements without electricity was obtained by comparing binary classified maps with resampled VIIRS night-time light imagery. The results revealed that the total area of human settlements without electricity in Bangalore City is approximately 36.57 sq. km. accounting for 6.2% of the total study area.